Magnetic resonance imaging (MRI) is an imaging technology in which signals are generated through the resonance of atomic nucleuses in magnetic fields. Due to its safety and preciseness, magnetic resonance imaging is widely used in the imaging field. Magnetic resonance parameter mapping provides a way to quantitatively analyze the biochemical characteristics of tissues. However, magnetic resonance parameter mapping has a low imaging speed due to the requirement for collecting a series of images. Therefore, its clinical application is limited.
Compressed sensing technology is an advanced technology which can speed up the data acquisition of magnetic resonance imaging. A magnetic resonance parameter mapping method based on compressed sensing may include two steps: image series reconstruction and parameter estimation. Due to the presence of undersampling and measurement noise, reconstruction error will be inevitably generated in state-of-the-art compressed sensing based image reconstruction, thereby the accuracy of the parameter estimation will be affected.